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dc.contributor.authorSchure, Mark B
dc.contributor.authorLindow, Janet C
dc.contributor.authorGreist, John H
dc.contributor.authorNakonezny, Paul A
dc.contributor.authorBailey, Sandra J
dc.contributor.authorBryan, William L
dc.contributor.authorByerly, Matthew J
dc.date.accessioned2019-12-13T18:46:59Z
dc.date.available2019-12-13T18:46:59Z
dc.date.issued2019-11-16
dc.identifier.citationSchure MB, Lindow JC, Greist JH, Nakonezny PA, Bailey SJ, Bryan WL, Byerly MJ Use of a Fully Automated Internet-Based Cognitive Behavior Therapy Intervention in a Community Population of Adults With Depression Symptoms: Randomized Controlled Trial J Med Internet Res 2019;21(11):e14754 URL: http://www.jmir.org/2019/11/e14754/ doi: 10.2196/14754en_US
dc.identifier.issn1438-8871
dc.identifier.pmid31738173
dc.identifier.doi10.2196/14754
dc.identifier.urihttp://hdl.handle.net/10150/636372
dc.description.abstractBackground: Although internet-based cognitive behavior therapy (iCBT) interventions can reduce depression symptoms, large differences in their effectiveness exist. Objective: The aim of this study was to evaluate the effectiveness of an iCBT intervention called Thrive, which was designed to enhance engagement when delivered as a fully automated, stand-alone intervention to a rural community population of adults with depression symptoms. Methods: Using no diagnostic or treatment exclusions, 343 adults with depression symptoms were recruited from communities using an open-access website and randomized 1:1 to the Thrive intervention group or the control group. Using self-reports, participants were evaluated at baseline and 4 and 8 weeks for the primary outcome of depression symptom severity and secondary outcome measures of anxiety symptoms, work and social adjustment, psychological resilience, and suicidal ideation. Results: Over the 8-week follow-up period, the intervention group (n=181) had significantly lower depression symptom severity than the control group (n=162; P<.001), with a moderate treatment effect size (d=0.63). Moderate to near-moderate effect sizes favoring the intervention group were observed for anxiety symptoms (P<.001; d=0.47), work/social functioning (P<.001; d=0.39), and resilience (P<.001; d=0.55). Although not significant, the intervention group was 45% less likely than the control group to experience increased suicidal ideation (odds ratio 0.55). Conclusions: These findings suggest that the Thrive intervention was effective in reducing depression and anxiety symptom severity and improving functioning and resilience among a mostly rural community population of US adults. The effect sizes associated with Thrive were generally larger than those of other iCBT interventions delivered as a fully automated, stand-alone intervention.en_US
dc.description.sponsorshipNational Institute of General Medical Sciences of the National Institutes of Health, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) [P20GM103474, U54GM115371, 5P20GM104417]en_US
dc.language.isoenen_US
dc.publisherJMIR PUBLICATIONS, INCen_US
dc.rights© Mark B Schure, Janet C Lindow, John H Greist, Paul A Nakonezny, Sandra J Bailey, William L Bryan, Matthew J Byerly. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.11.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCBTen_US
dc.subjectRCTen_US
dc.subjectdepression symptomsen_US
dc.subjectiCBTen_US
dc.subjectinternet-based cognitive behavior therapyen_US
dc.subjectrandomized controlled trialen_US
dc.subjectrural populationsen_US
dc.titleUse of a Fully Automated Internet-Based Cognitive Behavior Therapy Intervention in a Community Population of Adults With Depression Symptoms: Randomized Controlled Trialen_US
dc.typeArticleen_US
dc.contributor.departmentUniv Arizona, Coll Med, Dept Psychiaten_US
dc.identifier.journalJOURNAL OF MEDICAL INTERNET RESEARCHen_US
dc.description.noteOpen access journalen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleJournal of medical Internet research
refterms.dateFOA2019-12-13T18:47:00Z


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© Mark B Schure, Janet C Lindow, John H Greist, Paul A Nakonezny, Sandra J Bailey, William L Bryan, Matthew J Byerly. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.11.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as © Mark B Schure, Janet C Lindow, John H Greist, Paul A Nakonezny, Sandra J Bailey, William L Bryan, Matthew J Byerly. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.11.2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).